Investigating Heterogeneity in the Characterization of Risks Using Best Worst Scaling
Investigating Heterogeneity in the Characterization of Risks Using Best Worst Scaling
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DOI：
10.1111/risa.12012
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发表时间：
2013-09-01
期刊：
影响因子：
3.8
通讯作者：
Rigby, Dan
中科院分区：
文献类型：
--
作者：
Erdem, Seda;Rigby, Dan
本研究提出并实施了一种新的方法来引发和分析风险的感知。我们使用最佳最差尺度（BWS）来引出控制水平的受访者认为他们有风险和关注这些风险提示的水平。该方法寻求对大型风险集的控制和关注的感知，而启发方法的结构是为了减少与大型风险集排名相关的认知负担。BWS方法旨在对项目产生强烈的歧视。此外，该方法允许推导个人水平的值，在这种情况下，控制和担忧的感知，并分析这些如何随可观察特征变化，通过估计随机参数logit模型。该方法适用于20种食品和非食品风险。结果显示，在控制和担忧的认知上存在相当大的异质性，异质性的程度因风险而异，并且女性系统地认为自己对风险的控制比男性少。
This research proposes and implements a new approach to the elicitation and analysis of perceptions of risk. We use best worst scaling (BWS) to elicit the levels of control respondents believe they have over risks and the level of concern those risks prompt. The approach seeks perceptions of control and concern over a large risk set and the elicitation method is structured so as to reduce the cognitive burden typically associated with ranking over large sets. The BWS approach is designed to yield strong discrimination over items. Further, the approach permits derivation of individual-level values, in this case of perceptions of control and worry, and analysis of how these vary over observable characteristics, through estimation of random parameter logit models. The approach is implemented for a set of 20 food and nonfood risks. The results show considerable heterogeneity in perceptions of control and worry, that the degree of heterogeneity varies across the risks, and that women systematically consider themselves to have less control over the risks than men.